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Laser & Optoelectronics Progress, Volume. 60, Issue 20, 2018001(2023)

Fourier Ptychography Microscopy Based on Super-Resolution Adversarial Network

Yi Wang1,2, Xiaoyu Wei1、*, Baohui Liu1, and Hao Su1,3
Author Affiliations
  • 1College of Electrical Engineering, North China University of Science and Technology, Tangshan 063210, Hebei , China
  • 2Tangshan Technology Innovation Center of Intellectualisation of Metal Component Production Line, Tangshan 063210, Hebei , China
  • 3Tangshan Key Laboratory of Semiconductor Integrated Circuits, Tangshan 063210, Hebei , China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (8)
    Equations (10)
    References (24)
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    Figures & Tables(8)
    Fourier ptychography microscope system

    Fig. 1. Fourier ptychography microscope system

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    Structure of FPSRGAN's generator network model

    Fig. 2. Structure of FPSRGAN's generator network model

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    SE model

    Fig. 3. SE model

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    Structure of FPSRGAN's discriminator network model

    Fig. 4. Structure of FPSRGAN's discriminator network model

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    Loss curves for different combinations of loss functions

    Fig. 5. Loss curves for different combinations of loss functions

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    PSNR curves for different loss function combinations

    Fig. 6. PSNR curves for different loss function combinations

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    Amplitude and spectrum of simulation experiment results of different FPM reconstruction algorithms. (a) Original USAF1951 image; (b) center crop image of USAF1951; (c1) (c2) ground truth images; (d1) (d2) low-resolution images of the center of the forward imaging model; (e1) (e2) reconstruction images of the GS algorithm; (f1) (f2) reconstruction images of the AP algorithm; (g1) (g2) reconstruction images of the FPSRGAN algorithm

    Fig. 7. Amplitude and spectrum of simulation experiment results of different FPM reconstruction algorithms. (a) Original USAF1951 image; (b) center crop image of USAF1951; (c1) (c2) ground truth images; (d1) (d2) low-resolution images of the center of the forward imaging model; (e1) (e2) reconstruction images of the GS algorithm; (f1) (f2) reconstruction images of the AP algorithm; (g1) (g2) reconstruction images of the FPSRGAN algorithm

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    • Table 1. Reconstruction time, average PSNR, SSIM, and memory of each model on the validation set

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      Table 1. Reconstruction time, average PSNR, SSIM, and memory of each model on the validation set

      MethodTime /sPSNR /dBSSIMMemory /MB
      SRGAN612.760.59544763
      FPNET823.180.92475127
      FPSRGAN-DR41424.870.95985627
      FPSRGAN-SE-DR31425.460.95935509
      FPSRGAN-SE-DR41426.120.96605641
      FPSRGAN-SE-DR51525.030.95186190
      AP2215.010.9537
      GS5211.710.7826
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    Yi Wang, Xiaoyu Wei, Baohui Liu, Hao Su. Fourier Ptychography Microscopy Based on Super-Resolution Adversarial Network[J]. Laser & Optoelectronics Progress, 2023, 60(20): 2018001

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    Paper Information

    Category: Microscopy

    Received: Oct. 26, 2022

    Accepted: Dec. 23, 2022

    Published Online: Oct. 13, 2023

    The Author Email: Wei Xiaoyu (1347870676@qq.com)

    DOI:10.3788/LOP222900

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology